The focus of this article is the first item – creating an information framework that enables you to better serve, and keep, your customers by having the infrastructure that enables you to make the fullest and best use of your data.

Cordoba's latest book, Understanding the Predictive Analytics Lifecycle, offers an expert's look at the predictive analytics and new data technologies that foster customer loyalty and create revenue and tangible value in organizations.

The problem is that an organization may not be ready to take on this project. They often face bigger internal roadblocks than they realize. This can happen in a challenging, fast-paced, competitive market. This hyper-accelerated approach is further complicated by diminished IT investments that translate to a slow response to business needs.

To complicate the issue even more, systems are becoming more complex, not less, and data can overrun an ill-prepared team like an avalanche. Here are a few tips to help ensure that your deployment happens as quickly and effectively as possible.

Tip #1: Assess your organizational readiness and fill the gaps

As I mentioned earlier, leaders sometimes move faster than their organization’s resources will allow. These managers expect learning accelerators – templates, data models, toolboxes, power tools, etc. They want fast development cycles and customizations measured in days, not months. They expect constant communication on project status and expect project managers to have a can-do attitude. The reason for such high expectations? They have to create one vision and sell it to their internal customers.

Tip #2: Put the right team together before you start

To create an information framework, you need to engage internal resources in the early planning stages. They are the ones that will be gathering data from operational systems and mapping business needs to provide the right metrics into operational systems.&nbsp;

You will likely lack the internal expertise to pull together your own implementation, so choose a vendor carefully. They should be able to say: “I know your industry, I know your company, I know your competitors. I read and understood the letter to the shareholders. I read the letter of the chairman. I can create a compelling framework that will help you connect with your customer experience.”

It’s important that the vendor has a clear understanding of the delivery requirements. It is also essential to have qualified, experienced technical resources for data extraction, transformation, loading, reporting, visualization and analysis. In addition, the implementation team will need an efficient, integrated and complete set of software resources if they are going to deliver a framework of good quality on time.

Tip #3: Post-implementation support is vital

The ideal customer experience should be a clearly defined target, and the framework administrators will need extensive training from the implementation team if the system is to survive long-term.

Tip #4: Prove that it’s money well spent

The implementation team should have a clear business plan. They need to come to your leadership team with a clear picture of what the ROI will be. This means the cost of the project should align with value delivered. A solid project plan is important and needs to give executives a good idea of a timeline for the project. One useful technique for getting project buy-in is to hold a series of discovery sessions – brief workshops to break the ice and set reasonable expectations.

Technology plays a critically important role in the implementation of an effective customer experience strategy., but keep a watchful eye on the human factor. The four human-oriented tips presented here will help you and your organization deal with common customer experience projects pitfalls.

Al Cordoba, M.S., is the director of the SAS Center of Excellence at Truven Health Analytics. He has more than 25 years of experience in designing, planning, implementing and consulting on analytical projects.

Read More

Want to be more prepared when you're assessing vendors for data projects? Understanding the Predictive Analytics Lifecycle provides a checklist that contains more than 1,000 questions will be help you determine the best solution for your predictive analytics needs. Order it today.